STOCHASTIC DYNAMIC-PROGRAMMING TO SUPPORT SOW REPLACEMENT DECISIONS

In this paper a stochastic dynamic programming model, which runs on a personal computer, is introduced to determine the economic optimal rep lacement policy in swine breeding herds. This optimal policy maximizes the present value of expected annual net returns from sows present in the herd and from subsequent replacement gilts over a given planning horizon. Realistic dynamic programming replacement models include a la rge number of state and decision variables. A major issue in the under lying study has been how to cope with the resulting curse of dimension ality. An alternative dynamic programming model structure has been dev eloped and evaluated. Furthermore, a sensitivity analysis has been car ried out to achieve insight into possibilities for further reduction o f the model size. In this process, the quality of the results obtained are weighted against the amount of computation time needed to carry o ut the calculations.